Tax Incentives and the Price of Conservation*
Dominic P. Parker
University of Wisconsin-Madison
[email protected]
Walter N. Thurman
North Carolina State University
[email protected]
January 4, 2016
Abstract: We study the fastest growing type of conservation in the US: voluntary, permanent
restrictions on land use through conservation easements. Easements represent the largest
charitable gift on a per-donation basis, and their tax preference is controversial. We
incorporate federal and state income tax codes into a calculator to quantify the after-tax
donation price. Using a 1987-2012 panel, we measure the response of state-level easements
to the donation price. Our large elasticity estimates, spanning -2.0 to -5.1, indicate that tax
incentives induce conservation and do not merely subsidize it. We find no evidence that
generous tax benefits have induced lower-quality donations.
Key words: private provision of public goods, tax incentives, charitable donations, land use,
incentive-based conservation, conservation easements, land trusts
JEL Codes: H41, H31, L31, Q24
*We gratefully acknowledge the advice of Brent Stewart, Guido van der Hoeven, and Phil Harris, which
improved our understanding of the tax code. We also thank Dylan Brewer and Alexey Kalinin for compiling the
tax code and easement holdings data sets.
I. Introduction
The charitable donation incentive embedded in the U.S. income tax code is controversial
and the extent to which it impacts charitable giving is the subject of debate. According to
proponents of the deduction, it provides much-needed motivation for people to give to
nonprofits providing public goods in areas of environment, health, and the arts. Critics,
however, oppose the substantial subsidies it gives to wealthy donors and doubt that tax
considerations actually drive charitable giving.
Economists offer empirical findings relevant to the debate, estimating the responsiveness
of giving to changes in the after-tax “price” of donating, often specified as one minus the
marginal income tax rate. Although empirical conclusions vary, most studies suggest that
donors are quite responsive to tax benefits, with price elasticities usually varying from around
-0.5 to -2.0. 1 Elasticities are important because, when they are large, tax policy induces the
private provision of public goods at less than a dollar-for-dollar cost, perhaps by leveraging
the “warm glow” incentive to donate (Andreoni 1990, Saez 2004, Kotchen 2006).
In this paper, we study a particular class of charitable donation – the conservation
easement – for which tax preference is considered a generous and unnecessary subsidy to
wealthy landowners by its critics but a cost-effective incentive for protecting important
natural resources by supporters (see Bray 2010 and Eagle 2011). Conservation easements are
a private and voluntary form of land use zoning. They are legally binding agreements that
prevent landowners from subdividing rural land into residential and commercial lots; they
also typically regulate mining, forestry, and agriculture practices. 2 Although easements may
be sold by landowners, in practice they are usually donated. 3 Easements in the United States
1
A large number of studies estimate the “price” elasticity of charitable giving, measured in dollars, to temporary
and persistent changes in the tax code. Peloza and Steel (2005) summarize the range of elasticities in a metaanalysis, which covers 69 studies. The mean elasticity across these studies is -1.44. Studies estimating responses
to persistent changes in the tax code using panel data include Randolph (1995) (estimating an elasticity of about
-0.5), Auten et al. (2002), (a range from -0.4 to -1.26), Bakija et al. (2003) (an elasticity of about -2.0), and
Bakija and Heim (2011) (an elasticity of about -1). Elasticity estimates are important, because charitable tax
policy is considered “treasury efficient” when elasticities are greater than one (Steinberg 1990).
2
For in-depth legal descriptions of conservation easements, see Korngold (1984) and Dana and Ramsey (1989).
For descriptions of the range of easement terms, see Boyd et al. (2000), Parker (2004), and Rissman et al.
(2007). Conservation easements were pioneered in the United States but their use has been expanding into
various parts of world (see Korngold 2010, Rissman et al. 2015). Most prominently, conservation easements are
now in widespread use in Canada (Lawley and Towe 2014, Lawley and Yang 2015).
3
The value of easements, donated or purchased, is deemed to be the difference between the full market value of
the land and the encumbered value; parcels under easements typically lose 20 to 80 percent of their value.
1
are held by governments and by small, geographically dispersed non-profit organizations
known as land trusts, who are charged with enforcing easement compliance over time.
Our focus on conservation easement donations is important for several reasons. First, on a
per-donation basis, conservation easement donations now dwarf in value every other form of
charitable giving: works of art, real estate, and money. 4 Second, while easements represent
the fastest growing form of land conservation in the United States (see Table 1)—and they
are expanding internationally—the impact of tax incentives on growth has not yet been
quantified in a comprehensive way. Third, the peculiar institution of the conservation
easement encourages “dead hand control” of land because it requires land use restrictions to
be permanent and, unlike other forms of donation, not subject to reversal (Mahoney 2002,
McLaughlin 2005). This means that patterns of land conservation induced by even temporary
changes in tax incentives will have an enduring effect on future land use. Fourth, some have
worried that tax-driven easement donations lead to the wrong lands being conserved, because
land trusts may respond to ad hoc donation opportunities rather than adhering to planning
processes (Pidot 2005, Parker 2005, and Wolf 2012). More generally, the decentralized
approach to conservation has been criticized for its lack of transparency: the public does not
know how much it has paid for easements (through foregone tax revenues) nor does it know
what it has received in return (Merlenlender et al. 2004, Pidot 2005, and Bray 2010).
Our contribution to the understanding of conservation easements and the tax code can be
summarized along two dimensions. First, we quantify the generosity of tax incentives for
different landowners in different U.S. states by constructing a conservation income tax
calculator, spanning 1987 to 2012. 5 Conditional on taxpayer-specific information – e.g.,
income and the value of an easement donation –the calculator generates an estimate of the
after-tax “price of conservation.” This price incorporates all aspects of the tax code and is not
simply one minus the taxpayer’s marginal rate.
The calculator reveals sharp variation in the price of conservation over time and across
states due to changes in tax policy specifically directed toward easements, and due to changes
4
During the 2000s, the average value of a donated conservation easement was $491,000 compared to $163,000
for real estate and land, $45,000 for stocks and other financial gifts, $37,000 for intellectual property, and
$7,000 for art and collectibles (Eagle 2011).
5
Our calculator is the first that we are of aware of to quantify tax savings from easement donations over a long
panel, but Sundberg and Dye (2006) estimate tax prices for easement donations based on several cross-sectional
scenarios. Other scholars have developed calculators that estimate the price of charitable giving in general (see
Bakija 2009, Bakija and Heim 2011, Feenberg and Coutts 1993). The general calculators are not customized to
consider tax code features unique to easement donations, which are considered donations of real property with
special rules and provisions.
2
in federal and state income tax rates and rules about charitable deductions in general. For
example, for a landowner with annual income of $200,000 and an easement donation valued
at $500,000, the price of conservation ranges from a low of $0.16 per donated dollar
(Colorado in 2008) to a high of $0.56 (in the seven states lacking an income tax in 2003). The
calculator also quantifies the sensitivity of this price to landowner income. The highest price
of conservation is only $0.32 if the landowner’s income is $1 million rather than $200,000 in
the scenario above. We presume that after-tax prices are salient, as the term is used by Chetty
et al. (2009) and Chetty and Saez (2009), because information about tax implications is
readily available to would-be donors considering large donations of property.
Our second contribution lies in measuring the responsiveness of easement donations to
the after-tax price just described. We develop state-level panel data sets, spanning 1987-2012,
from a national database of conservation easement holdings by land trusts. Our empirical
analysis reveals large responses of easement holdings to changes in the donation price.
Characterized as long-run elasticities, our estimates range from around -2.0 to -5.1, based on
the percentage change in land trust easement holdings that corresponds to a one percentage
change in the donation price. The estimated elasticities are large and support the previously
untested assertion that tax incentives have driven land trust conservation. 6 For example, they
imply that federal tax code changes in 2006, which lowered the price of conservation by 7.5
percent, stimulated an increase of 38.7 percent in the annual flow of easement acres.
We also investigate the impact of tax incentives on the precision and quality of lands
conserved. We find suggestive evidence that land trusts will accept donations that they would
not choose to purchase. However, we find no evidence that easement donations induced by
lower after-tax prices of conservation are inferior in quality to other easement donations.
We begin the analysis in the next section by developing a theory of a landowner’s
decision to donate an easement. We discuss the empirical counterparts to the theoretical tax
regimes in section 3, where we also describe the tax calculator. We describe the data on land
trust holdings in section 4, and present empirical estimates of tax elasticities in section 5. In
6
Two recent unpublished studies examine the effects of tax incentives on land conservation, both viewing state
tax incentives as homogeneous and binary treatments. Soppelsa (2015) uses matching methods to relate tax
treatment to the stock of protected land in the Eastern U.S. Consistent with our results, she finds that counties in
treated states have a higher flow of land parcels into protected status. Suter et al. (2014) also treat tax incentives
as binary treatment and investigate the effect of such treatment on land trusts, as opposed to donors. They find
that trusts in states with tax credits are more likely to specialize in holding all-donated easement portfolios of
protected land, with no purchased easements. Sundberg (2011) uses a binary variable to identify states with tax
credit programs, and he finds increases in easements in those states during the mid 2000s.
3
section 6 we simulate the impacts of specific tax policies and test for the effects of tax policy
on the precision and quality of land trust conservation.
II. A Theory of the Supply of Open Space and the Price of Conservation
The decision by a landowner to donate a conservation easement constitutes a decision to
reallocate the landowner’s asset portfolio—between developable and permanently conserved
classes—in order to secure a preferred consumption stream. The adjustment in the asset
portfolio results in a change in the supply of open space amenities, which are managed by the
land trust that accepts the easement. Some land trusts play a more active role on the demand
side. They aggregate demands for open space from their monetary donors, they compete for
funding from government agencies, and they solve the collective action problems of
providing public and club goods (see Cornes 1996, Sundberg 2006) that are to a large extent
non-excludable and non-rival. The monetary donations trusts collect from their members are
used to fund the purchase of both capital assets (title to land and conservation easements) and
variable inputs in the provision of open space amenities.
To understand the effects of tax policy on land conservation, we focus on the supply side
described above. We first develop a static theory of the decision problem of landowners that
focuses on the tax-influenced price of land conservation. We then develop a dynamic
algebraic representation of the price of conservation, which is the conceptual counterpart to
the quantitative output of our tax calculator.
II.A.
The Price of Conservation in a Static Setting
Consider an agricultural landowner, depicted in figure 1, who derives utility from market
consumption W (for wealth) and from land conservation C. 7 The landowner’s single asset
consists of a parcel of land that generates an annual stream of farm income equal to I, which
has a capitalized value of I/r. The market value of the land is I/r + P, where P represents the
value of development rights. The landowner has a once-and-for-all opportunity to restrict
development on a portion of the land by placing on that portion a perpetual conservation
easement. The conserved portion is either retained and farmed or sold to someone who is
allowed only to farm the parcel. The complementary portion of land, which is not restricted,
is sold for its full market value.
We take the quantity of C consumed by the landowner to be the market value of the
7
Conservation here stands for any use of land that does not require development and building , e.g. agriculture
and forestry.
4
development rights extinguished by the easement. The value of the developable land sold
plus the present value of farm income on the remainder represents the wealth available to
purchase market goods and services. In a world without taxes, the budget constraint for the
landowner is:
(1) 𝑊𝑊 + 𝐶𝐶 = 𝑃𝑃 + 𝐼𝐼�𝑟𝑟 , 𝐶𝐶 ≤ 𝑃𝑃.
The inequality in (1) indicates that conservation is available only up to P, the value of the
parcel’s development rights.
This concept of conservation implies that while landowner utility increases with both
conservation and consumption of market goods and services, conservation is measured as the
dollar value of development rights extinguished. Assuming that P increases with the
likelihood of development, this means that extinguishing development rights on an acre
yields higher utility in locales where development is most imminent. 8 As indicated in the
diagram, in Regime 1 without taxes the tradeoff of wealth for conservation is one-for-one.
The implicit price of conservation in terms of foregone market consumption is PC = 1.
Regime 2 introduces a proportional tax on income at the rate 𝜏𝜏. Taxable income is
generated either by the sale of land or by farm earnings. Conservation is shielded from tax
because it represents potential market income permanently withheld from sale. Under the
tax, the budget constraint facing the landowner becomes:
(2) 𝑊𝑊 + 𝐶𝐶 = 𝑃𝑃 + 𝐼𝐼�𝑟𝑟 − 𝜏𝜏�𝑃𝑃 + 𝐼𝐼�𝑟𝑟 − 𝐶𝐶�, 𝐶𝐶 ≤ 𝑃𝑃.
Equation (2) can be rewritten as:
(3) 𝑊𝑊 + (1 − 𝜏𝜏)𝐶𝐶 = (1 − 𝜏𝜏)�𝑃𝑃 + 𝐼𝐼�𝑟𝑟�, 𝐶𝐶 ≤ 𝑃𝑃.
Equation (3) displays the income effect of the tax on the right-hand side and the change in the
relative price of conservation on the left. Now, 𝑃𝑃𝐶𝐶 = (1 − 𝜏𝜏). Figure 1 is drawn with
𝜏𝜏 = 0.3, implying that 𝑃𝑃𝐶𝐶 = 0.7. The indifference curve reflecting landowner preferences is
omitted in the second panel and in what follows in order to focus on changes in the budget
constraint and the price of conservation.
Regime 3 introduces the deductibility of charitable contributions. The U.S. federal
8
A parcel that will never come under development pressure cannot be conserved in this framework. The
development rights to the parcel have no market value, reflecting the fact that no action need be taken to keep
the parcel in its current undeveloped use. In contrast, an agricultural parcel at the rural-urban interface will have
high-value development rights, reflecting the likelihood of development absent intervention.
5
income tax code and most state income tax codes consider donations of conservation
easements to be charitable deductions, thus deductible with certain limitations. 9 This
constitutes a tax advantage beyond the shielding of C consumption from tax seen in Regime
2. The budget constraint in Regime 3 is:
or
(4) 𝑊𝑊 + 𝐶𝐶 = 𝑃𝑃 + 𝐼𝐼�𝑟𝑟 − 𝜏𝜏�𝑃𝑃 + 𝐼𝐼�𝑟𝑟 − 𝐶𝐶 − 𝐶𝐶�, 𝐶𝐶 ≤ 𝑃𝑃
(5) 𝑊𝑊 + (1 − 2𝜏𝜏)𝐶𝐶 = (1 − 𝜏𝜏)�𝑃𝑃 + 𝐼𝐼�𝑟𝑟�, 𝐶𝐶 ≤ 𝑃𝑃.
In the figure and in equation (5) there are no limits on the deductibility of charitable
contributions from taxable income. (The current federal tax code, and our empirical tax
calculator, recognizes the limitation that charitable contribution deductions cannot exceed
30% of adjusted gross income.) In Regime 3, the price of conservation can be seen to
decrease again to 𝑃𝑃𝐶𝐶 = (1 − 2𝜏𝜏).
Lastly, Regime 4 introduces a conservation tax credit, which mimics the credit programs
that a number of states have adopted: donating an easement creates a credit payable against
taxes in the amount of δC. The landowner’s budget constraint becomes:
or
(6) 𝑊𝑊 + 𝐶𝐶 = 𝑃𝑃 + 𝐼𝐼�𝑟𝑟 − 𝜏𝜏�𝑃𝑃 + 𝐼𝐼�𝑟𝑟 − 𝐶𝐶 − 𝐶𝐶� + 𝜏𝜏𝜏𝜏, 𝐶𝐶 ≤ 𝑃𝑃
(7) 𝑊𝑊 + (1 − 2𝜏𝜏 − 𝛿𝛿)𝐶𝐶 = (1 − 𝜏𝜏)�𝑃𝑃 + 𝐼𝐼�𝑟𝑟�, 𝐶𝐶 ≤ 𝑃𝑃.
In regime 4, 𝑃𝑃𝐶𝐶 = (1 − 2𝜏𝜏 − 𝛿𝛿). With τ = 0.30 and δ = 0.25, the implied price of
conservation is 𝑃𝑃𝐶𝐶 = (1 − 2 × 0.30 − 0.25) = 0.15, as illustrated in the figure. With high
enough marginal tax rates and tax credit rates, the price of conservation can become negative,
indicating that a landowner will encumber his land with easements even with no preference
for land conservation—the kink in regime 4 is optimal for any landowner for whom utility is
non-decreasing in C and W.
Empirical predictions of the effects of tax code changes follow from the implied changes
in the price of conservation and income. Consider the separate effects of changes in τ and δ.
An increase in τ rotates the budget line counterclockwise as shown in the move from regime
1 to regime 2 in figure 1. The increase in the tax rate will affect C positively through the
9
We focus on income tax benefits and do not formally consider capital gains tax benefits for two reasons.
First, easement donations provide minimal relief from federal capital gains taxes because IRS rules require the
owner’s basis to be adjusted downward by the fraction of the market value lost at the time of the donation.
Second, most states simply treat capital gains as identical to earned income, so the state income tax codes (that
we do model) apply to capital gains. (see Sundberg and Dye 2006).
6
decrease in PC and negatively to the extent that the income elasticity of demand for C is
positive. While these effects are partially offsetting, an increase in only the marginal rate in a
progressive tax code would primarily have a price effect and could be expected to increase C
consumption, hence, conservation easement donations. An increase in 𝛿𝛿, while also reducing
the price of conservation, has no effect on potential market income (𝑃𝑃 + 𝐼𝐼/𝑟𝑟): a
counterclockwise rotation of the budget constraint as show in the move from regime 3 to
regime 4, with the fixed point of the rotation being on the vertical axis. Thus an increase in 𝛿𝛿
would have an unambiguous positive effect on C through both price and income effects.
The comparative statics and relative sizes of the price and income effects can be
understood by writing the budget constraint (7) for the general case of regime 4 as:
(8) 𝑊𝑊 + 𝑃𝑃𝐶𝐶 𝐶𝐶 = 𝑀𝑀,
where 𝑃𝑃𝐶𝐶 = (1 − 2𝜏𝜏 − 𝛿𝛿) and 𝑀𝑀 = (1 − 𝜏𝜏)�𝑃𝑃 + 𝐼𝐼�𝑟𝑟�.
The proportionate change in the price of conservation due to a change in 𝜏𝜏 is:
𝜕𝜕 ln 𝑃𝑃𝐶𝐶 �
−2�
𝜕𝜕𝜕𝜕 =
(1 − 2𝜏𝜏 − 𝛿𝛿) ,
(9)
and the proportionate change in potential market income is:
(10)
𝜕𝜕 ln 𝑀𝑀� = −1�
𝜕𝜕𝜕𝜕
(1 − 𝜏𝜏).
Even in this flat tax case, the proportionate decline in 𝑃𝑃𝐶𝐶 caused by an increase in 𝜏𝜏 is larger
than the proportionate decline in 𝑀𝑀. In the illustrated case with τ = 0.30 and δ = 0.25, an
increase of one percentage point in the tax rate (from 0.30 to 0.31) would result in a 13.3%
decline in 𝑃𝑃𝐶𝐶 but only a 1.43% decline in M. Only if the demand for C were much more
income elastic than price elastic would the net effect of an increase in 𝜏𝜏 be to reduce C. 10
The more likely effect is that an increase in the proportional tax rate would increase C, hence,
increase easement donations.
Again from (8), the proportionate change in the price of conservation due to a change
in 𝛿𝛿 is:
(11)
𝜕𝜕 ln 𝑃𝑃𝐶𝐶 �
−1�
𝜕𝜕𝜕𝜕 =
(1 − 2𝜏𝜏 − 𝛿𝛿) ,
but the proportionate change in potential market income is:
(12)
10
𝜕𝜕 ln 𝑀𝑀� = 0.
𝜕𝜕𝜕𝜕
Specifically, the income elasticity of demand for C would have to be positive and more than 13.3/1.43 = 9.3
times as large as the Marshallian price elasticity of demand in order for the net effect on C to be positive.
7
Therefore, an increase in the rate of tax credit unambiguously increases the donations of
easements, assuming that the Marshallian own-price elasticity of demand for C is negative.
II.B.
A Dynamic Price of Conservation
Donating an easement implies a commitment to a permanent reduction in the landowner’s
income and a temporary tax benefit that accrues only until the deductions and tax credits are
exhausted. An empirically useful theory must account for this fact.
Consider an infinitely-lived landowner who is considering donating an easement on all of
his land. If he chooses not to donate the easement, he sells all his land in time 0 and his
income thereafter is the annualized return on the unrestricted market value of the land:
𝑟𝑟(𝑃𝑃 + 𝐼𝐼�𝑟𝑟) = 𝑟𝑟𝑟𝑟 + 𝐼𝐼, where r is the market rate of return on investment. The landowner’s
after-tax income under the proportional tax system is 𝑟𝑟𝑟𝑟 + 𝐼𝐼 − 𝜏𝜏(𝑟𝑟𝑟𝑟 + 𝐼𝐼).
If the landowner makes a donation in the amount C, then his perpetual gross income
becomes 𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼. Assuming that he can fully deduct the donation from taxes in year 0,
the year of the donation, then his after tax income in that year is 𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼 −
𝜏𝜏[𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼 − 𝐶𝐶)]. Because the deduction is fully absorbed by his year-0 income, his
after-tax income in later years reflects the reduced income implied by the donation, but
without the tax benefit. After tax income in years 1 and beyond falls to 𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼 −
𝜏𝜏[𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼)].
To calculate the price of conservation in this dynamic setting, we compare the present
value of the dollar value of market consumption (W in the static model) under the with- and
without-donation scenarios. To do so, and to motivate the development of our tax calculator,
which takes into account the dynamic complexities of progressive federal and state tax codes,
we introduce the following notation. Replace the tax term 𝜏𝜏(𝑟𝑟𝑟𝑟 + 𝐼𝐼) with the more general
term 𝑇𝑇0𝑤𝑤𝑤𝑤 , which stands for taxes owed on without-donation income (𝑟𝑟𝑟𝑟 + 𝐼𝐼) with 0
deductions. Similarly let 𝑇𝑇𝐶𝐶𝑤𝑤 represent the taxes owed on with-donation income (𝑟𝑟(𝑃𝑃 − 𝐶𝐶) +
𝐼𝐼) in a year in which C is deducted from taxable income. And let 𝑇𝑇0𝑤𝑤 represent taxes owed on
with-donation income in years after the easement-related deductions have been exhausted
when deductions from taxable income are 0.
Using this notation, the streams of after tax income for the landowner under the with- and
without-donation scenarios are:
8
Income without donation
Income with
donation
Difference
𝑟𝑟𝑟𝑟 + 𝐼𝐼 − 𝑇𝑇0𝑤𝑤𝑤𝑤
𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼 − 𝑇𝑇𝐶𝐶𝑤𝑤
𝑟𝑟𝑟𝑟 − (𝑇𝑇0𝑤𝑤𝑤𝑤 − 𝑇𝑇𝐶𝐶𝑤𝑤 )
𝑡𝑡 = 0
𝑟𝑟𝑟𝑟 + 𝐼𝐼 − 𝑇𝑇0𝑤𝑤𝑤𝑤
𝑡𝑡 = 1, … , ∞
𝑟𝑟(𝑃𝑃 − 𝐶𝐶) + 𝐼𝐼 − 𝑇𝑇𝑜𝑜𝑤𝑤
𝑟𝑟𝑟𝑟 − (𝑇𝑇0𝑤𝑤𝑤𝑤 − 𝑇𝑇0𝑤𝑤 )
The difference in present value between the two after-tax income streams is the present
value of the “Difference” column above:
(13) 𝑃𝑃𝑃𝑃 𝑤𝑤𝑤𝑤 − 𝑃𝑃𝑃𝑃 𝑤𝑤 = 𝐶𝐶 − �
𝑇𝑇0𝑤𝑤𝑤𝑤 −𝑇𝑇𝐶𝐶𝑤𝑤
1+𝑟𝑟
1
𝑇𝑇0𝑤𝑤𝑤𝑤 −𝑇𝑇0𝑤𝑤
+ 1+𝑟𝑟 �
𝑟𝑟
��
= foregone wealth – PV of tax saving .
The present value calculation assumes that all flows are received at the ends of the periods
and that the PV is calculated at the beginning of period 0, when the decision is made.
Denote the bracketed term on the right-hand side of (13), the PV of tax savings, as
ΔT. In the following section we describe how we calculate the price of conservation as:
(14) 𝑃𝑃𝐶𝐶 ≡
𝐶𝐶− ΔT
𝐶𝐶
=1-
ΔT
𝐶𝐶
,
where the components of ΔT—the three counterfactual tax calculations 𝑇𝑇0𝑤𝑤𝑤𝑤 , 𝑇𝑇𝐶𝐶𝑤𝑤 , and 𝑇𝑇0𝑤𝑤 —
are generated from our detailed federal and state tax calculator.
III.
The Conservation Income Tax Calculator
In this section, we quantify the income tax incentive to donate conservation easements
using our income tax calculator, which spans 1987-2012. Here we review the incentives
provided by both federal and state tax codes, describe our construction of the tax calculator,
and present results on the price of conservation.
III.A. Overview of Income Tax Incentives
Federal income tax deductions for easements received statutory authorization in 1976. 11
The tax advantage of a contribution depends on the filer’s marginal tax rate, which varies
with income in the federal progressive tax structure and has also varied over time due to
changes in tax law. In our calculations, higher marginal tax rates (τ) will lower the price of
conservation. Further, the magnitude of tax advantage from charitable contributions is, in
many instances, limited by a taxpayer’s Adjusted Gross Income (AGI) and affected by rules
11
Under § 170(h) of the internal revenue code (IRC), donated easements are required to preserve land for one of
the following general purposes: outdoor recreation, wildlife habitat, scenic enjoyment, agricultural use, or
historic importance. Importantly, the deduction is only permitted if the conservation easement is granted in
perpetuity.
9
that govern the carryover of unused tax deductions into subsequent tax years. Prior to 2006,
federal law capped the deduction amount a landowner could claim at 30 percent of his or her
AGI each year for six years.
Federal legislation passed in 2006 increased income tax benefits for easements donated in
2006 through 2012. The new law raised the deduction landowners can take from 30 percent
of their AGI in any year to 50 percent, and to 100 percent for qualifying farmers and
ranchers. The law also extended the carry-forward period for a donor from five to fifteen
years. As we see below, these changes in the federal tax code have lowered the price of
conservation for a subset of taxpayer AGI scenarios.
Income tax incentives at the state level have varied significantly across states and across
time. Due to the deductibility of state income taxes from federal returns (and the deductibility
of federal taxes from some state returns), the federal and state donation incentives interact.
At a snapshot in time, in 2012, figure 2 categorizes state income taxing structures to
match the theoretical regimes described in figure 1. There are seven states that did not tax
income. These states correspond to regime 1. There are 11 states that taxed income, but did
not allow the itemization of charitable deductions, including conservation easements. These
states correspond to regime 2. There are 22 states that taxed income and allowed charitable
deductions, corresponding to regime 3. There are 11 states that offered tax credits to donors
of conservation easements, meaning that δ > 0 in our theoretical setup. These 11 tax credit
states correspond with regime 4 in figure 1. 12 As figure 2 indicates, all of tax credit programs,
except North Carolina, began after 2000. North Carolina’s program began in 1983, prior to
our sample period and was terminated in 2014. Note that the federal system corresponds to
regime 3 and is overlayed on top of the state systems.
The state tax credit programs (see appendix A) allow a taxpayer to take a percentage of
the value of an easement and use it as a dollar-for-dollar credit toward payment of state
income taxes. Some of these tax credit programs allow both a deduction and a tax credit for
the easement donation. The tax credit programs provide for tax credits of between 25% and
100% of an easement’s value, with various overall limits on the deductions. The terms of tax
credit programs vary considerably across states and over time, as do the rules pertaining to
their carryover into future tax years. In four states (Colorado, New Mexico, South Carolina,
and Virginia) the tax credits are transferable, meaning that an AGI-constrained donor can sell
credits to a non-donating taxpayer who is not so constrained. This effectively eliminates the
12
State tax credit programs exist, or have existed, in 14 states, but only 11 offered income tax incentives.
10
limitations imposed by percent-of-AGI rules written into the tax credit laws, and lowers the
price of conservation relative to a situation in which the percent-of-AGI rules and
carryforward limits are binding constraints.
III.B. Constructing the Tax Calculator
Accounting for the net tax advantage from a donation requires a unified calculation of
federal and state income taxes, both with and without the donation. To do so, we have created
a tax calculator that relies on historical data on the state and federal income tax systems from
1987 to 2012. The calculator, written in Matlab, takes as input the real Adjusted Gross
Income of a hypothetical taxpayer and the value of the taxpayer’s conservation easement
donation. It calculates the federal and state tax bills for the taxpayer, taking into account the
federal deductibility of state taxes and any state tax credit available. 13
For federal taxes, the calculator reads in tax brackets, tax rates, personal exemptions, and
standard deductions for 1987-2012 as provided by the Tax Foundation. 14 The calculations
assume the taxpayer is married filing jointly, takes the standard deduction, and claims two
personal exemptions. In the easement donation case, deductions from income are extended
beyond the standard deduction by the appraised value of the easement.
To account for changes in the value of the dollar, the assumed AGI of the taxpayer and
the value of the donation are adjusted to 2012 constant-dollar terms. Limits on deductions
and carryover rules make the tax calculator dynamic and turn the tax benefit calculation into
a present value calculation. For example, charitable donation deductions were limited to 30
percent of AGI in tax years 1987-2005. In those years, if the value of deductions exceeded 30
percent of AGI, the unused deduction could be carried into the next tax year. The calculator
assumes that the taxpayer makes no additional easement donation in the following year but
does use the carried over deduction to reduce taxable income. This process is followed in
subsequent years until either the entire deduction is used, or until the time limit on carryover
is reached. Prior to 2005, deductions could be carried over for up to five years. In 2006, the
carryover wall was increased to 15 years. Tax benefits that accrue in future years are
discounted back to the current year at an annual rate of 5 percent.
13
We do not recommend that our tax calculator be used as a substitute for TurboTax as it ignores some features
of the tax code—features that we think are unimportant in consideration of the tax incentives to donate. To the
extent that the tax code features we ignore would change by equal amounts the with- and without-donation tax
bill, our calculation of the tax advantage to donation is unaffected by our abstraction from the actual code. The
following subsections are intended to allow the reader to independently assess the extent to which we have
captured the tax code features that influence the tax advantage to donation.
14
http:www.taxfoundation.org/publications/show/151.html
11
Although the discussion above begins with the federal tax calculation, the sequence used
in our tax calculations begins by calculating the state tax liability for the given AGI taxpayer,
both with and without the assumed donation. The state taxes are then deducted from income
taxable at the federal level. Note that this deviates from reality in that when calculating the
current federal tax bill one actually deducts state taxes paid in the previous year. Here we
make a streamlining assumption that the current year’s state taxes are deducted from the
current year’s federal taxable income, an assumption that we regard as neutral with respect to
the with- and without-donation tax comparison.
To account for state tax systems, we have transformed data on each of the 50 states over
1987-2012 into a schedule of tax brackets and tax rates using the annual “All States Tax
Handbook” published variously in different years by Prentice Hall and by the Research
Institute of America. We rely on the same handbooks as a data source for documenting
whether or not the state recognized itemized charitable deductions in a given year. In those
states and years that levied an income tax and allowed deduction of charitable contributions,
we assume the percentage-of-AGI limitations and the carryover limits at the state level were
the same as those at the federal level. 15
Aside from the four categories of states illustrated in figure 2, the tax calculator tracks
other, more subtle, differences. The nuanced tax systems that we account for are: (1) states in
which state income tax is a fixed fraction of a filer’s federal tax, (2) states that tax wage and
dividend income at different rates, (3) states in which personal exemptions are taken in the
form of tax credits, (4) states that have easement tax credit programs that allow filers to take
both the charitable donation and the tax credit, (5) and tax credit states that allow either a
deduction or a credit, but not both (filers are assumed to take the credit). States also switch
categories over time—notably those states that institute easement tax credit programs—and
the tax calculator tracks those changes.
For those states that draw a distinction between wages on the one hand, and interest and
dividend income on the other, the calculator arbitrarily assumes that half of AGI is wage
income. Finally, the calculator assumes that easement donors in the four states that allow the
sale of tax credits sell their credits for 85 cents on the dollar, a figure consistent with
observation on the selling prices of transferable credits.
15
Some states allow the deduction of federal taxes from state taxable income (eight states in 2012); however,
the tax calculator makes the simplifying assumption that federal taxes are not allowed as deductions from state
taxable income.
12
III.C. Calculator Output
We represent the tax incentives to donate through an after-tax Price of Conservation
Index, defined in section 2, equation (14) as follows:
where
𝑃𝑃𝐶𝐶 ≡
𝐶𝐶− ΔT
𝐶𝐶
=1-
ΔT
𝐶𝐶
,
ΔT = 𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 𝑤𝑤𝑤𝑤𝑤𝑤ℎ𝑜𝑜𝑜𝑜𝑜𝑜 𝑎𝑎 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 − 𝑃𝑃𝑃𝑃 𝑜𝑜𝑜𝑜 𝑡𝑡𝑡𝑡𝑡𝑡 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 𝑤𝑤𝑤𝑤𝑤𝑤ℎ 𝑎𝑎 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑,
taking as given the taxpayers AGI and the appraised value of the easement donation, C. The
variable PC measures the dynamic after-tax price per dollar of easement donation.
Figure 3illustrates the price of conservation for the seven states lacking income taxes (see
figure 2), for four different taxpayers: ones with AGIs of $100,000, $200,000, $350,000, and
$1 million. 16 Because the states have no income tax, the tax benefits from an easement
donation flow entirely from the federal code.
To focus first on the role of marginal tax rates, we assume the donation value in panel A
is only $1,000 so that the taxpayer never runs into the limitations imposed by the percent-ofAGI limits. A donation of $1,000 is below 30% of AGI for even the lowest-AGI taxpayer.
For a small enough donation, the price of conservation becomes an algebraic transformation
of the relevant marginal tax rate. Setting C = $1,000 in the expression above yields:
𝑃𝑃𝐶𝐶 ≡
𝐶𝐶− ΔT
𝐶𝐶
= 1 −
ΔT
𝐶𝐶
𝜏𝜏
= 1 − �𝜏𝜏 + 1+𝑟𝑟�
= 1 − 2 𝑥𝑥 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑡𝑡𝑡𝑡𝑡𝑡 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑖𝑖𝑖𝑖 𝑟𝑟 = 0.
The expression differs from the price of conservation in regime 3 (see figure 1) due to the
receipt of tax benefits over time, which results in a discounted term. 17
Panel A of figure 3 shows the calculator output. Focusing first on the end of the sample
period, the year 2012, we see the price of conservation declines with the taxpayer’s AGI. The
highest line shows the after-tax price per dollar of donation to be $0.512 cents for the
taxpayer with an AGI of $100,000. The marginal rate for this taxpayer was 25 percent, and
the calculation is 𝑃𝑃𝐶𝐶 = 1 – 0.25 – 0.25/1.05 = 0.512. By contrast, the taxpayer with an AGI of
16
The website of the IRS categorizes easement and real estate donations by AGI categories. Of the 15,580
returns that donated real estate and easements, show that 40% came from taxpayers with AGI < $100,000, 23%
from taxpayers with AGI between $100,000 and $200,000, 21% from taxpayers with AGI between $200,000
and $500,000, 6% from taxpayers with AGI between $500,000 and $1,000,000 and 10% from taxpayers with
AGI > $1 million. See www.irs.gov/uac/SOI-Tax-Stats-Special-Studies-on-Individual-Tax-ReturnData#noncash.
17
The price of conservation is calculated based on tax rates and tax rules during the year of the contribution.
Taxpayers are assumed to expect current rates and rules to reign in the future. Our empirical analysis in the next
sections considers the possibility that taxpayers are able to anticipate future changes in the tax code.
13
$1 million paid a marginal rate of 35 percent, so her price of conservation in 2012 was 𝑃𝑃𝐶𝐶 = 1
– 0.35 – 0.35/1.05 = $0.317. 18
Panels B and C shows the calculator output for taxpayers in the same set of states, but
who are now making a donation appraised at C = $500,000 and $1 million respectively. 19 The
price of conservation in these cases is more complicated than above, due to the AGI
limitations on deductions and the carry forward limits. Comparing panels B and C with panel
A shows that the price of conservation tends to increase with donation value, especially for
the lower income donors. Prior to 2006, the price of conservation increased with donation
size primarily because of the 5-year carry forward limit. Because of the AGI limits and the
carry forward constraints, the taxpayer with AGI = $100,000 could deduct only 0.30 x
$100,000 = $30,000 each year for six years, leading to a total deduction of $180,000.
Moreover, the $30,000 deductions made in years 1-6 yield declining financial benefits due to
the 5 percent discount rate, from the perspective of a would-be donor considering a donation
in the current time period. The price of conservation falls for the lower income donors in
2006 primarily because the carry-forward period was extended from 5 to 15 years. The AGI
limitation was also increased for qualifying farms and forests from 30 to 100 percent. Hence,
a qualifying landowner with AGI = $100,000 would fully exploit the $500,000 donation in 5
years, resulting in a decrease in the price of conservation from 0.69 to 0.64. 20
Appendix B includes graphs of the price of conservation in each of the 50 states and
Figure 4 summarizes that output by comparing the mean price across states with the four tax
regimes. We focus on a landowner with an AGI of $200,000 and assume he owns a
qualifying farm or forest. We allow the donation size to vary as before, from $1,000 to
18
The increases in the price of conservation across all AGI categories from 2001-2003 are due to tax rate cuts
during the George W. Bush administration. The sharp rise and then decline in the price of conservation at the
higher AGIs during 1987-1993 reflect changes in tax rates and brackets initiated by the Tax Reform Act of
1986, and the Omnibus Budget Reconciliation Acts of 1990 and 1993. The 1986 legislation lowered the top
marginal rate from 38.5 percent to 28 percent but introduced a “rate bubble” of 33 percent for a range of
incomes spanning approximately $140,000 to $290,000 in 2012 CPI adjusted dollars. This bubble explains why
our $200,000 AGI taxpayer faced a lower price of conservation during 1987-1991. The 1990 Omnibus
legislation increased the top tax rate to 31 percent in 1991 and eliminated the bubble, and the 1993 Omnibus
legislation increased the top marginal tax rate to 39.6 percent in 1993, which explains the decline in the price of
conservation for high AGI taxpayers after 1993.
19
The contribution values compare with the mean donated easement value of $475,416 during 2003-2012 based
on IRS data reported at www.irs.gov/uac/SOI-Tax-Stats-Special-Studies-on-Individual-Tax-ReturnData#noncash.
20
The landowner benefits from the carryforward extension but can be harmed by the requirement that he must
donate the full $100,000 each year. He could be better off if he was allowed to spread the $500,000 donation
over more years, allowing him to eliminate his tax liability for a longer time span. We thank Guido van der
Hoeven for helpful discussions on this point.
14
$500,000 to $1 million. There are three take away points from figure 4. First, the price of
conservation predictably falls as we move from regime 1 (no state income tax), to regime 2
(no charitable deduction allowed), to regime 3 (deduction allowed but no credit), to regime 4
(tax credit states). Second, most of the time series variation is driven by changes in the
federal code and by the introduction of tax credits in some states. For the tax credit states, the
mean price begins to fall in 2000 and there is a gradual decline through 2012. The gradual
decline is mostly due to additional states adding tax credits over time. The mean price does
monotonically fall within tax credit states, however, because some credit programs fluctuated
in generosity over time as states experimented with different rules and constraints. Examples
of experimenting states include California, Colorado, and Virginia (see appendices A and B).
The third take away point is that some subtle time series variation occurs within states in
regimes 2 and 3 due to changes state income tax rates and brackets. These changes are
difficult to decipher in figure 4, but appendix B illustrates changes over time in some regime
2 and 3 states, including Montana, North Dakota, and Rhode Island. We exploit all of this
state level time-series variation in our econometric analysis of easement donations.
IV. Data on Conservation Easement Holdings
We have created state-level panel data sets indicating the number and acres of easement
acquisitions by land trusts over 1987-2012. The acres measure is arguably more useful than a
dollars-donated measure because acres more closely approximate the open space ‘output’ of
land trusts. Hence, our analysis differs from other studies of the response of charitable giving
to tax policy in that we more directly measure the relationship between tax policy and public
good provision. One advantage of our approach is that acres held is a more verifiable result of
tax policy, when compared to dollars donated (see Fack and Landais 2016).
The ideal annual state-level panel data set for our purposes would span all land trust
holdings of conservation easements and it would indicate which parcels were donated and
which were purchased. We do not have this ideal data set. We have, however, constructed
three annual state-level panels that come close to the ideal in different respects. Table 2
summarizes the strengths and weaknesses of each data set.
The first data set—the TNC data set—is national in coverage and includes all easement
acquisitions made by the Nature Conservancy. The Nature Conservancy (TNC) is the
country’s largest trust, holding approximately 23 percent of land trust conservation easements
in 2010. TNC provided us with data on their holdings of easements and owned land at the
county level, on an annual basis, from 1987 to 2012. In addition to being national in
15
coverage, the strength of the TNC dataset is that it indicates which easement parcels were
donated and which were purchased. The weakness is that it represents the actions of one land
trust rather than all land trusts.
The second data set—the NCED data—is from the National Conservation Easement
Database. According to the NCED website, it is
“the first national database of conservation easement information, compiling records
from land trusts and public agencies throughout the United States.... This effort helps
agencies, land trusts, and other organizations plan more strategically, identify
opportunities for collaboration, advance public accountability, and raise the profile of
what’s happening on-the-ground in the name of conservation.” 21
The strength of the NCED dataset is that it includes information on the location of
easement holdings and the year of acquisition across the entire country. The weakness is that
the data coverage of easement holdings is presently incomplete. Some land trusts have not yet
sent spatial GIS files to the NCED and not all of the data sent to the NCED have been
mapped. 22 In a robustness check, we show that our estimates are similar when we weight the
regression results by the proportional completeness of easement coverage for each state,
which we estimate to range from a low of 1 percent to a high of over 95 percent in several
states based on comparisons of NCED easement acreage in 2010 with acreage reported in the
Land Trust Alliance census of all land trusts that year as described below.
The variation in estimated completeness, at the state-level, is not correlated with our
state-level variables of interest. In 2010, the correlation between completeness of NCED
coverage and our price of conservation is only 0.09, based on the AGI and value of donation
assumptions we use in the calculation of the price. The correlation between the NCED
coverage and the stock of easements held by land trusts in 2010, according to the Land Trust
Alliance census during that year, is only -0.004. These low correlations assuage concerns that
our estimates based on the NCED data are biased by incomplete coverage.
There is a third data set—the LTA dataset—that we do not employ in the panel
regressions but do use is in our assessment of the precision and quality of land trust
conservation. The Land Trust Alliance (LTA) is a trade organization for land trusts, with over
1,500 members. On an irregular basis, every several years, LTA surveys its members. While
21
http://conservationeasement.us/about
22
According to the NCED website, easements that are known yet not in NCED because: 1) they have not been
digitized, 2) they were withheld from NCED, or 3) the NCED team is still working with the easement holders to
collect the information.
16
the questions asked have evolved over successive surveys, LTA has since 1984 asked their
member how many acres of land they hold in conservation easements, and how many they
hold in fee simple. The LTA provided us with the results of their eight surveys since 1984. 23
The weakness of this data set is that we cannot construct an annual panel from it.
Consequently we do not employ LTA data in our primary regressions because we are
interested in the dynamic effects of tax code changes and cannot infer those effects from the
irregular LTA panel.
We know that the majority of conservation easements acquired by land trusts were
donated to them, but we can exploit information on the month of acquisition in the NCED
data set to further identify which easements were likely donated. The month of acquisition is
a useful indicator because easement donations (and charitable donations in general) tend to
occur disproportionately in December, at the end of the tax year. Evidence of this is found in
the TNC data, which indicate the month of acquisition and whether the easement was donated
or purchased. Figure 5 shows the distribution of TNC easement acquisitions during 1987 to
2012. After dropping the 257 easements that were coded as “partial gifts”, there remain 1,238
TNC easements that were full donations and 590 that were full purchases. Of the full
easement donations to TNC, 58 percent were acquired in December. By comparison, only 20
percent of the easements purchased by TNC were acquired in December. Overall, 45 percent
of TNC’s easements were acquired in December. 24
Although we cannot observe whether easements in the NCED dataset were purchased or
donated, the database indicates the month of acquisition. Of the 8,723 NCED easements
acquired during 1987-2012 with month of acquisition data, we note that 43 percent were
acquired in December. 25 In the next section, we separately estimate the response of
December easements to the price of conservation.
Figure 6 shows the count and acreage of easements acquired over time in each of the two
datasets. The figure indicates that NCED contains more easements and more easement
acreage. There are 13,346 NCED easements in the data compared to 2,080 in the TNC data.
The NCED easements cover 5.47 million acres compared to 3.17 acres in the TNC data. The
average size of a TNC easement is 1,524 acres compared to 410 acres for the NCED land
23
The LTA surveys yield information on trust holdings in 1984, 1990, 1994, 1997, 2000, 2003, 2005 and 2010.
24
Thought of another way, 86 percent of TNC’s easements acquired in December were donated. By contrast, 53
percent of TNC’s easements acquired in other months were donated.
25
Thirty-five percent of the easements in the NCED dataset indicate the year but not month of acquisition.
17
trusts. This difference highlights the fact that TNC tends to operate at a larger scale than the
relatively small, local land trusts that hold the majority of the NCED easements.
Table 3 shows summary statistics for the panel data sets and it highlights two statistical
issues that we confront in our empirical analysis. First, there are several state-year
combinations for which the outcome variables are zero in the TNC and NCED data sets.
Second, there are clearly large outliers in acres acquired – for example, the 610,814 acre
maximum in the NCED data sets reflects an enormous forestry easement acquisition in
Maine, during 2001. The 244,753 acre maximum in the TNC data set reflects a large
ranchland easement acquisition by the TNC, in New Mexico during 2004 (Parker and
Thurman 2011). In part to mitigate the influence of outliers such as these, we log the acreage
data in our empirical analysis. Another benefit of logging the acreage is that this gives us a
way to standardize the acreage data across states that vary considerably in area and hence
have different ultimate constraints on easement acquisitions. Logging the data, however,
raises questions about how to handle the observations with values of zero. We deal with this
issue by employing the inverse hyperbolic sine transformation. Except for values very close
to zero, the inverse hyperbolic sine is approximately equal to log(2y) so it can be interpreted
in the same way as a standard logarithmic dependent variable. The inverse hyperbolic sine
provides the benefit of being defined at zero, allowing us to retain the information contained
in the y = 0 observations (see Burbidge et al. 1988, MacKinnon and Magee 1990).
V. Empirical Analysis of Tax Incentives
To motivate the potential importance of state variation in the tax code in explaining
private conservation, we begin by presenting graphical evidence. Next, we estimate panel
regression models.
V.A. Graphical Evidence
Figure 7 compares the annual flow of easement acquisitions in the TNC and NCED data
sets across tax credit and non-tax credit states. Panels A and B compare the mean counts and
panels C and D compare the mean acreage. To normalize for differences in the land area of
states, we have divided acreage flows by the number of privately owned acres. 26 The vertical
line is at 1999, the year before states (other than North Carolina) began introducing new tax
credit programs.
26
The “private acres” denominator is the sum of acreage held by the federal government plus state owned parks
and recreation land. We treat the denominator here as time invariant and use the stock of government land
holdings in 2000 for the calculations.
18
In panels A and B, there is visual evidence that the introduction of tax credits triggered an
increase in the count of easements acquired by land trusts. Prior to 1999, the trajectories in
easement donations were similar across the two categories of states. Beginning in 2000,
however, the flow of easements expanded in the tax credit states and the gap in means
between the two types of states widened.
The relative pre-tax credit and post-tax credit trends are less clear in panels C and D,
which show acreage flows. The spike in 1994 is due to a large ranchland transaction in New
Mexico, a tax credit state that launched its program in 2004. The spike in 2001 and 2002 is
due, in part, to a large forestry conservation easement in Maine, which does not have a tax
credit program. If one ignores these two prominent spikes, then Panels C and D show that the
mean acreage was trending similarly across the two types of states until around 2000, after
which there was relative growth in acreage in the states with tax credits.
All of the panels in figure 7 show a prominent spike in easement acquisitions in 2007,
across both tax credit and non-tax credit states. We note that 2007 is the first full year in
which taxpayers could take advantage of the extension of the carryforward period from five
to fifteen years. (The enhanced tax benefit was passed in August 2006 and retroactively
available to donations made earlier in 2006). The observed spike in 2007 suggests that donors
responded in 2007 rather than 2006.
Figure 7 suggests two other possible dynamic responses to changes in the price of
conservation. First, in some panels there appears to be a decline in easements in the year prior
to a decrease in the price of conservation. This suggests that potential donors may have
temporarily withheld their easement donations in anticipation of forthcoming donations
prices. Panel A and especially panel B also suggests that the flow of easement acquisitions
may have responded to short-run changes in the price of conservation—rather than long-run
decreases in the level—given the expanding and then shrinking gap between the flow of
easements in tax credit and non-tax credit states during 2000-2012. We explore these
dynamic issues below in the regression analysis. We also explore the response of easement
acquisitions to changes in the price of conservation induced by state income tax rate and
bracket changes, which are less easy to visualize graphically when compared to tax credit
induced variation.
V.B. Econometric Model
Our basic strategy is to estimate an equation of the form:
(15)
Ihs( easements )it = ai + φt + ωi t + β1∆ ln Pi ,t +1 + β 2 ln Pit + β 3∆ ln Pit + X ith + e it .
19
Here i refers state and t refers to year. The notation “Ihs” refers to the inverse hyperbolic
sine. The notation P is the “price of conservation” index.
We allow each state to have its own time invariant intercept ( α i ) to control for
geographic, topographical, cultural, and institutional differences across states that are
relatively constant across time. We also allow for time-shocks that might affect rates of
easement donations across all states ( φt ). Such factors include changes in the federal estate
tax code, national recessions, and informational shocks about the ecological value of land
conservation. In some specifications, we include state-specific linear time trends ( ωi t ) to
control for possible trends in easement flows prior to income tax code changes.
We employ the index generated from a donation of $500,000 from the owner of a
qualifying farm or forest with an AGI of $100,000 (all in 2012 dollars). We choose this
combination because it induces the best econometric fit among the combinations displayed in
figures 3 and 4, based on comparisons of adjusted R-squared from estimates of equation (15).
The assumed value of $500,000 is close to the mean value of actual easement donations
during 2003-2012, which was $475,416. 27 The AGI value of $100,000 may seem low, but
IRS summary data shows that 81 percent of all U.S. farm returns were from filers with AGI
less than $100,000 and 94 percent were from filers with AGI less than $200,000. 28 The same
IRS data indicates that 63 percent of easement donations came from taxpayers with AGI of
less than $200,000 in 2012.
The β 2 coefficient is of key interest. It measures the persistent response in the flow of
easement donations to a persistent change in the price of conservation. We expect β 2 < 0.
Because the price of conservation is logged, and the dependent variables are transformed by
the inverse hyperbolic sine function, β 2 is a long-run “price” elasticity.
The other coefficients attempt to measure dynamic responses in a parsimonious way.
Following Bakija and Heim (2011), we control for the possibility that donors respond to
expected changes in the price of conservation in the year preceding the change. Hence, β1
measures the anticipatory response of easement donations to a future change in the price. We
expect β1 > 0 if donors can anticipate future changes and withhold (or move forward)
donations when the donation price is expected to decrease (increase) in the next period. The
27
See www.irs.gov/uac/SOI-Tax-Stats-Special-Studies-on-Individual-Tax-Return-Data#noncash.
28
These data are from 2007, and are reported in table 1 of Cain (2011), available at www.irs.gov/pub/irssoi/11inbystatesprbul.pdf.
20
coefficient β3 measures any additional first-period response to a change in the price of
conservation beyond the long-run effect. Hence, the period-t effect of a change in the tax
code is β 2 + β3 , which is a one-time increase in the stock of easements. If potential donors
think a favorable change in the tax code may be temporary, then we should observe β3 < 0 as
donors act quickly to exploit the change in donation price.
The variables in X include state-year level controls for a land price index, population,
farm income, forest income, total per capita income, and government acquisitions of
conservation easements through purchasing programs. Table A1 in the appendix provides
summary statistics, definitions, and data sources.
V.C. Main Results
Table 4 shows our first set of regression estimates. The dependent variable is the count of
easement acquisitions. Columns 1-6 employ TNC data and columns 7-10 employ NCED
data. All estimates include the set of covariates, and columns 4-6 and 9-10 add state specific
linear trends. These are our preferred estimates because including time trends improves the
goodness of fit of all regression models. The standard errors in all estimates are clustered at
the state level to control for possible serial correlation in the error structure within states
(Bertrand et al. 2004). In these estimates we omit the tax bubble years of 1987-1991 because
the estimates during those years are much more sensitive to the choice of donation and AGI
combinations. Hence, our estimates focus on the 1992-2012 panel of 21 years. 29
We begin by interpreting the β̂ 2 coefficients, theresponse of easement flows to a change
in the price of conservation . Starting with column 5, which is our favored estimate of the
TNC data, there is a persistent negative relationship between the price of conservation and
the flow of all conservation easements, donated and purchased, to TNC. The estimate is a
statically precise and economically large elasticity of -1.48. For comparison, the dependent
variable in column 6 is the count of easements purchased by TNC. The estimate in this
column serves as a placebo test. We do not expect purchases to be directly influenced by a
state’s tax price of conservation if in fact the price is causally related to easement flows rather
than non-tax influences that also drive easement donations to land trusts. The placebo
regression in column 6 show that persistent changes in the tax code are unrelated to TNC
29
While the goodness of fit is best for the AGI= $100,000, donation = $500,000 scenario for 1992-2012, the fit
is better for a higher income scenario during the bubble tax years of 1987-1991. This may be because
conservation easement donations were relatively more concentrated among higher income donors in the early
years of land trusts, compared to today. Rather than using different AGI scenarios for different years, we
employ a simpler procedure and hold constant the AGI and donation size scenario over time.
21
purchases because β̂ 2 is effectively zero. This null finding raises confidence that the columns
4-5 coefficients are not simply driven by unobserved, demand-side drivers of easement
acquisitions.
The β̂ 2 long run elasticity estimates are larger in our favored estimate of the NCED data,
which is given in column 9 at -2.00. This is our favored estimate because it employs all of the
NCED data and includes state-specific time trends. Comparing the NCED β̂ 2 estimates
against those of TNC, we see that the long run response of easement counts to tax policy is
greater for the smaller, local land trusts that comprise the NCED data set. This finding
suggests the smaller trusts are more dependent on donations, which is consistent with the
observation that TNC has a large budget for purchases whereas many smaller trusts do not.
Turning now to the dynamic effects of tax policy, consider the estimates of β̂1 and β̂3 .
There is no evidence of a significant anticipatory effect as β̂1 is imprecisely estimated and
not distinguishable from zero in all columns. There is, however, evidence of a stronger
response to the price of conservation in the first-period following a tax code change. In
columns 5 and 9, β̂3 is negative and statistically significant indicating the flow of donated
easements surged in the first year of a tax price decline. This surge may indicate that
landowners consider tax benefits to be potentially temporary, and therefore move quickly to
exploit them. The positive estimate of β̂3 in column 6 is interesting. This means that TNC
purchased fewer easements in the first year of a decline in the tax price of easements. This
result suggests that a new tax credit, or a lower tax rate, may crowd out easement purchases,
at least temporarily.
Turning briefly to the coefficient estimates on the controls in table 4, which are not our
focus, we note the following patterns. First, the land price index is negatively related to
easement donations in some specifications. This finding is consistent with our tax price
estimates because, in our price of conservation index, higher development values raise the tax
price of conservation. Second, farm and forest income are positively related to easement
flows in some specifications. These findings are consistent with our tax price estimates
because, in our price of conservation index, higher income from farming or forestry lower the
price of conservation. While the other covariates are not significantly different from zero in
any specification, we emphasize that their inclusion or omission from the regressions has
very little impact on the β̂1 , β̂ 2 , and β̂3 coefficients of interest.
22
Table 5 shows regressions estimates of easement acres, rather than counts. The
specifications and right-hand side controls are identical to those in table 4 and the price of
conservation coefficients are again elasticities. In general the patterns in table 5 mimic those
in table 4 but there is a key difference. The long run elasticities of β̂ 2 for donated easement
acres tend to be much larger in magnitude than those for donated easement counts but these
acreage elasticities are also less precisely estimated.
We turn first to the TNC coefficients in table 5, focusing on column 5. The β̂ 2 and β̂3
coefficients are negative and economically large but imprecisely estimated, with t-statistics of
1.29 and 1.55 respectively. The sum of the two coefficients is significant, however, with a tstatistic of 1.95. Taken together, these results mean that a decrease in the tax price induces a
surge in acreage donated to TNC in the first year following the tax change. In the longer run,
however, the lower tax price does not continue to influence the flow of acreage donated to
TNC. How does this result reconcile with the statistically significant column 5 estimate of β̂ 2
= -1.48 in table 4? Apparently, prospective TNC donors of large easements are more
immediately responsive to changes in tax prices than are prospective TNC donors of small
easements. This may be because large easement donors have more to lose if they don’t act
quickly to exploit tax benefits that could be temporary. 30
Turning to the NCED tax price estimates in columns 9, we note the long run β̂ 2 elasticity
is large, at -5.11 in column 9 compared to a statistically insignificant elasticity of -1.81 for
TNC acres in column 5. This means that the long-run flow of easement acreage to small,
local land trusts is more sensitive to tax prices when compared to the long-run flow to TNC.
The first-period response ( β̂ 2 + β̂3 ) is larger for TNC: at -6.98 versus -5.89. The fact that
TNC easements tend to be larger than NCED easements helps explain this difference,
assuming that large landowners are more anxious to quickly exploit decreases in easement
donation prices.
To summarize the findings in Table 4 and 5, we find large, negative elasticities with
respect to persistent changes in the tax price of conservation. For the NCED data, which
include a comprehensive set of land trusts, our favored estimates is -2.00 for easement counts
and -5.11 for easement acreage. These estimates quantify how the long-run flow of easements
responds to a percentage change in the tax price of donations. Because easements are
30
The incentive to act quickly could be especially strong for large donors because many of the tax credit
programs cap the aggregate value of claimed credits at the state-year level, perhaps inducing a race among large
donors to become eligible before the cap is exceeded.
23
perpetual, the long-run stock is also important. For the NCED data, our favored elasticity
estimate indicates that the long-run stock of acres would increase in addition to the flow
response, by the percentage change in the price x 5.98.
The elasticity estimates summarized above are conditional on covariates and state specific
time trends and they are robust to placebo tests of easement purchases by TNC. Although the
placebo and time trends results help to justify a causal interpretation of β̂1 , β̂ 2 , and β̂3 in the
donated columns of tables 4 and 5, we perform more robustness checks below.
V.D. Threats to Identification and Robustness
There are four reasons why our estimates above might not identify causal effects of the
tax code. First, there is measurement error in the NCED data due to incomplete reporting, and
this error possibly is correlated with the price of conservation over time within a state. To
address this possibility, we weight the baseline regression results by our estimates of the
proportion of all land trust easements reflected by the NCED data, at the state level. Panel B
of table 6 reports the results and shows that our main findings are similar with and without
these weights.
Second, it may be the case that easement donations were trending differently in tax credit
and non-tax credit states prior to the enactment of credits. For example, if easement donations
were already on a faster trajectory in tax credit states prior to 2000, then our β̂ 2 coefficients
could be biased away from zero. Evidence that this was not the case is found in figures 6 and
in the fact that adding state specific linear time trends to the regressions in table 4 and 5 did
not generally move the β̂ 2 coefficients towards zero in the donation specifications.
To further probe the role of pre-existing time trends, we create a ‘false timing’ placebo
test. For the tax credit states, we move the tax price forward two time periods so that our
placebo variables falsely imply a premature onset of tax credit programs. Next, we eliminate
the state-year observations during which the tax programs were actually in place. The
resulting tests, shown in panel C of table 6, indicate there was not a response of easement
donations to future tax policy in the two years preceding the onset of the actual tax credit
programs. This finding adds to our confidence that actual tax policy, rather than pre-existing
trends, explain the sharp increase in easement donations during the tax credit years.
A third threat to identification is the omission of time-varying, state specific estate tax
controls. At the federal and state level, estate taxes can affect the after-tax price of
conservation easement donations in particular (see Sundberg and Dye 2006) and of charitable
bequests in general (see Bakija et al. 2003, Joulfaian 2000). Hence, the omission of state
24
estate tax measures could bias our coefficients on income tax prices if within-state time
variation in estate tax policy is correlated with within-state time variation in income tax
policy. We do not have long panel data on state-level estate and inheritance tax rules, but we
do know which states followed federal estate tax rules and which states had stand-alone estate
taxes. This is significant because states following federal rules phased out their estate tax
along with the federal government over 2002-2005. States with stand-alone estate taxes did
not, and some states introduced new estate taxes between 2005 and 2012. 31 Based on this
information, we create a simple time-varying indicator variable. The variable is equal to one
for state-year combinations for which a state had an estate tax. Otherwise, the variable is
equal to zero. As panel D of table 6 shows, adding the estate tax control has virtually no
impact on the baseline coefficients of interest suggesting there is little correlation between
estate tax changes and changes in our income tax price of conservation. 32 We conclude that
the omission of estate tax prices is not biasing our overall estimates. 33
The fourth threat to identification has a less obvious technical solution. It is possible that
states implementing tax credit programs were more predisposed to easement growth than
were states that did not, even absent tax policy changes. Perhaps states that implemented tax
credit programs had more active land trust lobbyists, for example. The potential endogeneity
problem here is that successful land trust lobbyists are also plausibly better at recruiting and
soliciting easement donations.
To address this possible source of endogeneity we construct a set of ‘counterfactual’
states that ‘almost’ implemented easement tax credit programs prior to 2012. This list of
states is provided in Pentz (2007). She provides a detailed assessment of state conservation
tax credits. According to Pentz (2007), five states: Idaho, Nebraska, West Virginia,
Kentucky, and Minnesota were either working to create programs or had actually attempted
to pass conservation tax credit legislation during our period of analysis. Based on her
account, these five states may comprise a better set of counterfactual states than the entire
31
The information comes from www.taxadmin.org/fta/rate/estatetax.html.
32
In the panel D column 7 specification, the coefficient on the estate tax measure is 0.103 and statistically
significant at p<0.1, suggesting the indicator is associated with a 10 percent increase in easement flows. The
coefficients on the estate tax variable in the other columns tend to be positive but imprecisely estimated,
suggesting the role of estate tax is more complicated than characterized by our simple indicator variable.
33
There are also property tax benefits from donating a conservation easement but these benefits are difficult to
characterize in a meaningful way at the state level. Moreover, most owners of agricultural land can receive
property tax benefits from current use assessments without making an easement donation. For these reasons, we
do not attempt to measure property tax benefits here but refer the reader to descriptions of the issues in
Sundberg (2014).
25
sample of the 40 non-tax credit states. Panel E shows regression estimates that employ a
subsample of sixteen states: the eleven tax credit states and the five counterfactual states
listed above. Importantly, the β̂ 2 elasticity coefficients tend to be larger in absolute value
than those estimated in the baseline. The coefficient estimates in panel E are also a bit more
precisely estimated, which is surprising because the sample size is small, with only 16 states.
Panel F shows the regression estimates when we rely on only “variation in the timing of
treatment” to identify the income tax price coefficients. 34 The panel F sample comprises only
the 11 tax credit states. The logic here is to assume the tax credit states constitutes a valid set
of counterfactual states for each other, but that the timing of the onset of tax credit programs
(and the timing of changes within the programs) are random. Hence, the identification of the
coefficients in this subsample is exclusively from variation in the arguably random timing of
policy changes. As panel F shows, using this approach does not change our key conclusions
relative to the baseline estimates that employ full sample.
Panel G displays the final robustness check. Observations from states and years with tax
credits in force are taken out of the sample, as are the years before tax credits take effect.
Variation in the price of conservation in the resulting sample come from variations in the tax
code that are not solely aimed at conservation. The resulting estimates of β 2 , the long run
elasticity, are statistically insignificant in table 6. We interpret this to mean that the powerful
statistical identification in our data set comes more from the tax credit changes than from
year-to-year variation in marginal tax rates. This may be because tax credits are more
‘salient’ than changes in marginal tax rates, thereby inducing a clearer response (see Chetty et
al. 2009). The fact that the first-period responses ( β 2 + β3 ) tend to be larger in the sample
without tax credits suggests that donors may view changes in tax rates to be more temporary
than new tax credit programs. Further, the finding that the no-tax-credit β 2 estimates tend to
be smaller or positive than their with-tax-credit counterparts in the acreage estimates of
columns 5-8, is consistent with the fact that reducing the price of conservation through
enacting a tax credit will have a positive income effect on easement donations, whereas
reducing the price of conservation through an increase in marginal income tax rates will have,
if anything, a negative income effect. Thus the total measured effect from variation due to
tax credits should be, and is found to be, larger than the effect from variation due to tax rates.
To summarize, our findings are robust to a suite of robustness checks. Although we
34
Variation in timing approaches, or VAT, are commonly used in labor and education policy applications (see,
e.g., Hoynes and Schanzenbach 2009, and Almond et al. 2011).
26
cannot rule out every possible source of endogeneity, the most straightforward interpretation
of the β̂ 2 and β̂3 estimates is that they represent the average causal effect of income tax
policy on conservation easement donations.
VI. Aggregate Acreage Outcomes and the Quality of Easement Donations
In the introduction, we note that preferential tax treatment towards easements has been
criticized for its lack of transparency: the public does not know what it has gained in terms of
protected land, nor does it know how much it has paid for easements (through foregone tax
revenues) (Merlenlender et al. 2004, Pidot 2005, and Bray 2010). Further, some have
wondered if tax-driven easement donations lead to the wrong lands being conserved, because
land trusts may respond to ad hoc donation opportunities rather than adhering to planning
processes (see Pidot 2005, Parker 2005, Wolf 2012).
We provide here simulations of the aggregate effects in states that adopted tax credits
based on our baseline short and long run elasticity estimates of -5.9 and -5.1: the percentage
response of the flow of easement donations to a one percentage change in after-tax price of
conservation. And we ask whether the quality of land preserved—as defined by individual
land trusts—is influenced by tax incentives.
Table 7 shows the simulated changes due to the introduction of the tax credit programs
actually instituted by states. In Colorado, for example, the new tax credit program lowered
the price of conservation for our representive landowner (AGI = $100,000, easement
donation = $500,000) by 30 percent, relative to the price in the year preceding the program.
Our elasticity estimates imply a short run acreage increase of 200 percent and a long-run
increase of 168 percent. Calculations for other states follow the same procedure. Note that all
calculations are based on the change in price induced by the initial tax credit program; most
of the programs were modified in subsequent years in ways that significantly changed the
price of conservation (see appendices 2 and 3).
Table 7 also simulates the changes induced by the federal tax code changes in 2006. For
our representative landowner, assumed to be a qualifying farmer, the changes lowered the
price of conservation by 7.5 percent and stimulated a long-run acreage increase of 38.7
percent. This simulation illustrates how a modest change in the tax code can stimulate a large
increase in annual acreage flows, and hence an even larger eventual increase in the stock of
permanently restricted land.
With respect to the quality of easement conservation induced by tax incentives, it is
27
important to recognize that the tax incentive to donate easements is just that—an incentive to
donate easements—and not necessarily to donate ecologically or aesthetically valuable openspace amenities. Just as in the incentive contracting literature (e.g., Baker 2008) the agent (a
landowner in our case) is paid to contribute towards an output that can be measured (the
acreage of easements), which is not exactly what the principal (the public) is seeking. It is,
perhaps, “the folly of rewarding for A while hoping for B.”
This implies that land trusts, which intermediate between landowners and consumers of
land-based amenities, determine the effect of tax policy on conservation quality. If land trusts
accept all easement offerings, regardless of quality, and stronger tax incentives induce
donation offerings of marginal quality, then increased tax incentives will disproportionately
increase the flow of low quality easements. If land trusts are selective and focus their limited
resources on high-quality easements, however, then increased tax incentives could
disproportionately decrease the flow of low-quality easements, by allowing trusts to choose
quality offerings from a larger set of prospective donors.
A detailed analysis of the impact of tax incentives on the quality of easement acquisitions
is beyond the scope of our study, but we shed some empirical light here. To do so, we exploit
data from Land Trust Alliance (LTA) survey questions about conservation outcomes in their
2005 “census of land trusts.” Trusts were asked to categorize the source of their easement
holdings: purchased, donated, or bargain sale (a mix of the other two.) Of the subset of trusts
who answered the question, the mean percentage of easements acquired by donation was
79.5%; 13.6% on average were purchased; and 6.9% were acquired through bargain sales
(see table 8). Evidence that acquisition methods reported in the LTA survey reflect tax policy
is found in Table A2 of the appendix. There we find that trusts operating in states with lower
prices of conservation hold a greater number of donated easements (consistent with the
findings of Sutter et al. 2014) and there is no relationship between purchased easements and
the price of conservation.
Table 8 also reports a measure of conservation quality. Trusts were asked to report the
percentage of their easement acreage in areas identified by the trust as conservation priority
areas. According to the sample average, 75.3% of trust-held easements were located in areas
deemed to be priority areas. The answer to this question gives a quantitative measure of the
conservation importance of a trust’s holdings, allowing trusts to self-identify what is
important to their principals.
Table 9 uses cross-section regressions at the trust level to connect this measure of quality
to the method by which easements are acquired, and to link this to the after-tax price of
28
conservation. The first column of table 9 regresses the percent of a trust’s holdings in priority
areas on the percent of easements donated, and on the percent acquired by bargain sale, while
controlling for the size of the trust. The residual category–purchased easements–is omitted.
The donation percentage variable is statistically significant suggesting that every one
percentage point increase in a trust’s holdings coming from donations (at the expense of
purchases, given that bargain sales is held constant) results in a 0.172 reduction in the
percentage of land held in a conservation priority area. The effect of shifting one percentage
point from purchases to bargain sales has a smaller measured effect: -0.086, an estimate
roughly 1.3 times the size of its standard error. The ordering of coefficient makes sense and
supports the interpretation that donated easements are inferior easements, according to the
trust’s definition of the term. The positive coefficient on the number of easements held
suggests that larger land trusts are better at attracting land in priority areas. Similar results are
found in the second column of table 9, which weighs the estimates by the size of land trusts.
Columns 1 and 2 of table 9 provide evidence that donated easements are inferior to
purchased easements. They do not tell us if the particular easements induced by generous tax
benefits differ in quality from other donated easements. To probe this issue, we first divide
the price of conservation relevant to a trust’s prospective donors into quartiles, ranked by the
price averaged over 2000 to 2005 from lowest to highest. Next, we create indicator variables
for each quartile, which we interact with the percentage of a trust’s easements acquired via
donation. (For trusts operating in multiple states, the price of conservation is averaged across
states). By comparing the coefficients across these interaction terms, we can assess the
sensitivity of the relationship between donated and priority-area easements to the generosity
of the tax code.
If trusts in states with low prices of conservation accepted unusually low-quality
easements, we should see a larger effect of the “percentage donated” on “percent of easement
in priority areas” in those states. If anything, we see the opposite. Column 3 shows
statistically significant negative effects of donations on easement quality in all four quartiles
(donated easements are inferior to purchased easements), but no more so for trusts in states
with the strongest tax incentive (the lowest prices of conservation.) The point estimate of the
effect is the largest in the quartile with the weakest tax incentives. Further evidence comes
from column 4, in which land trusts are weighted by their acreage held. Column 4 shows
insignificant effects of donations on quality for trusts in the lowest three lowest quartiles of
the price of conservation. The statistically significant column 4 coefficient of -0.300 for the
fourth quartile suggests that donated easements are inferior to purchased easements only in
29
those states whose donors face a high price of conservation. This provides suggestive
evidence that tax incentives increase the quality of easement donations, insofar as “quality” is
defined by land trusts through their priority areas. 35
VII.
Conclusion and Implications
Governments have long acted to protect land from development on a city’s urban-rural
interface, sometimes through direct acquisition (national, state, and local parks) and in other
instances through land use regulation (see Turner et al. 2014 and Glaeser and Kahn 2004).
But less centralized, incentive-based conservation approaches are becoming more common
across the globe. 36 The U.S. system of preferential tax treatment towards conservation
easements held by local land trusts is a leading example of decentralized conservation. In it,
the government’s main role is to set tax policy and then let voluntary actors, under limited
regulation, determine the quantity and patterns of permanent conservation.
Our analysis informs policy debate about this decentralized method of conservation in
two ways. First, some critics worry that generous tax policies toward easements merely
subsidize wealthy landowners, and do not change land use decisions. Our tax calculator
quantifies the incentives across different income categories and shows that high-income
landowners do accrue substantially higher tax benefits from donating when compared to landrich but cash-poor landowners. But our large elasticity estimates, ranging from -2.0 to -5.1,
are inconsistent with the view that tax incentives simply subsidize rich landowners without
changing their behaviour. On the contrary, the elasticity estimates indicate that tax policies
lowering the price of donating easements induce large increases in the annual flow of
permanently conserved tracts of land. We conclude that tax incentives are a key driver of
easement and land trust growth across and within U.S. states.
Second, other critics worry that tax-induced conservation leads to ad hoc patterns of land
use restrictions instead of more valuable coordinated networks of protected land. Our analysis
reveals mixed evidence about this concern. On one hand, we find that trusts accept easement
donations outside of conservation priority areas that they would not purchase. 37 On the other
35
We recognize that “quality” is complex and multi-dimensional, and that it may not be fully characterized by
priority areas. For more on measuring the quality of easement donations, see Lawley and Yang (2015).
36
Many governments are now paying landowners to voluntarily refrain from making land use changes through
incentive based programs (Salzman 2005, Jack et al. 2009, Alix-Garcia et al. 2016, Gjersten et al. 2015).
37
It is an empirical question if conservation networks accrued through the land trust system of relying on tax
donations differ from centrally planned networks that may be chosen by a public or private organization with a
large budget for purchasing land, see Costello and Polasky (2004) and Newburn et al. (2006).
30
hand, there is no evidence that increasing tax incentives leads to a greater proportion of
easements outside of priority areas.
Our analysis raises questions about the limits of decentralized and private conservation
and how its performance compares with centralized approaches. Although a full comparative
analysis is outside the scope of the current study, these questions strike us as important,
especially because direct government conservation may crowd out (or crowd in)
decentralized private conservation (see Albers et al. 2008, Parker and Thurman 2011).
Moreover, although we do not investigate the role of enforcement over charitable donations,
evidence elsewhere indicates that lax oversight over tax fraud can affect claims of charitable
giving in other settings (see Fack and Landais 2016). In our setting, increasing Internal
Revenue Service oversight over fraudulent conservation easement appraisals in recent years
may have decreased the responsiveness of easement donations to stronger tax incentives. We
leave this important issue for future research.
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34
Figure 1:
Budget Constraints of Landowner under Four Tax Regimes
Figure 2:
State Income Tax Regimes in 2012
#
*
#
MA=2011
2008
2001
DE=2000
2000
2000
MD=2001
1983
*
2004
2001
#
#
2006
Regime 1: No income tax
Regime 2: Tax but no itemization
Regime 3: Tax with itemization
Regime 4: Tax credits
Notes: Dates indicate when the initial tax credit legislation was first in force. # indicates that states have conservation
easement specific tax incentives, but ones that are relatively weak and not based on income taxes. * indicates the state only
taxes dividend and investment income but not wage income.
Figure 3:
Price of Conservation due to Federal Tax Policy
(For AGI=$100K, $200K, $350K, and $1 million in states without income taxes)
.1
.2
.3
.4
.5
.6
.7
Panel A: Donation = 1K
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
.1
.2
.3
.4
.5
.6
.7
Panel B: Donation = 500K
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
.1
.2
.3
.4
.5
.6
.7
Panel C: Donation = 1 M
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Notes: The legend is as follows. AGI $100,000 is the red solid line. AGI $200,000 is the black dotted line. AGI
$350,000 is the blue long dash-dotted line. AGI $1,000,000 is the green dashed line. We assume the AGI
$100,000 and AGI $200,000 donors are qualified farmers and the higher AGI donors are not.
Figure 4:
Mean Price of Conservation in States with the Four Tax Regimes
.1
.2
.3
.4
.5
.6
Panel A: AGI = 200K Donation = 1K
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
.1
.2
.3
.4
.5
.6
Panel B: AGI = 200K Donation = 500K
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
.1
.2
.3
.4
.5
.6
Panel C: AGI = 200K Donation = 1 M
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Notes: The legend is as follows. The red solid line denotes the mean across the 7 states without income taxes
(regime 1). The black dotted line shows the means across states that have income taxes but do not allow
itemized charitable deductions (regime 2). The blue dash-dotted line shows the means across states that have
income taxes and allow itemized charitable deductions (regime 3). The green dashed line shows the means
across states that introduced easement specific tax credits (regime 4).
Figure 5:
Distribution of Nature Conservancy Easement Acquisitions across Months, 1987-2012
Full Purchase
400
0
200
Number Acquired
600
800
Full Donation
J
F M A M J
J A S O N D
J
F M A M J
J A S O N D
Month
Notes: The letters on the horizontal axis indicate the first letter of each month. Reading from left to
right, J = January and so on. The data come from the Nature Conservancy. The left hand panel shows
the distribution of easements that were “All Gift” according the TNC. The right hand panel shows the
distribution of easements that were neither “All Gift” nor “Partial Gift”, meaning these easements were
purchased.
Figure 6: Conservation Easements Acquired by Land Trusts
B: Count of Donated Easements
0
0
100
500
200
300
1000
400
1500
500
A: Count of Easements Acquired
1987
1990
1993
1996
1999
2002
2005
2008
1987
2011
1990
1993
1999
2002
2005
2008
2011
2008
2011
0
0
400000
150000
800000
1996
D: Acres of Donated Easements
300000
C: Acres of Easements Acquired
1987
1990
1993
1996
1999
Nature Conservancy
2002
2005
2008
NCED
2011
1987
1990
1993
1996
1999
2002
Nature Conservancy
Notes: Here the “donated” acres in the National Conservation Easement Database (NCED) refer to those acquired in December.
2005
NCED
Figure 7: Comparison of Mean Easements Acquired in States with and without Tax Credits
A: Count of TNC Easements
0
0
2
10
4
20
6
30
8
40
B: Count of NCED Easements
1987
1990
1993
1996
1999
2002
2005
2008
2011
1987
1990
1996
1999
2002
2005
2008
2011
D: NCED Easement Acres; % of Private Land
0
0
.01 .02 .03 .04 .05
.02 .04 .06 .08 .1
C: TNC Easement Acres; % of Private Land
1993
1987
1990
1993
1996
1999
States with Credits
2002
2005
2008
2011
States w/o Credits
1987
1990
1993
1996
1999
States with Credits
Notes: The vertical line signifies 1999, which is the final year before states began introducing new tax credit programs.
2002
2005
2008
2011
States w/o Credits
Figure 8: Time Response of Easements to Change in the Price of Conservation
Easementst = a + β1∆Pt +1 + β 2 Pt + β3 ∆Pt
( β1 > 0, β 2 < 0, β3 < 0)
Flow of Easements
Counterfactual Flow
Price of Conservation
Time
t-1
t
t+1
Table 1
Comparison of Government and Land Trust Holdings
Change
% Change
1990 Acres
2010 Acres
1990-2010
1990-2010
358,891,255
368,047,552
9,156,296
2.55
Bureau of Land Management
168,223,327
171,186,890
2,963,563
1.76
US Forest Service
165,790,139
167,598,134
1,807,995
1.09
20,179,876
24,380,375
4,200,499
20.82
4,697,914
4,882,153
184,239
3.92
32,522,280
31,298,245
-1,224,035
-3.76
0
2,311,702
2,311,702
na
7,895,296
10,526,759
2,631,463
33.33
2,165,041
7,681,198
5,516,157
254.8
793,137
13,392,500
12,599,363
1588.6
Four Federal Land Agencies
US Park Service
US Fish and Wildlife Service
Federal Programs
Conservation Reserve
Wetland Reserve
State Parks*
Land Trusts
Outright Ownership
Conservation Easements
Notes: *Denotes the data are for 2007 rather than 2010. The federal land data come from Payment and
Lieu of Taxes (PILT) records of the US Department of Interior. The federal land program data come
from the U.S. Department of Agriculture. The state parks data come from the US Census. The
conservation easement data come from files sent to the authors from The Nature Conservancy and data
from the periodic Land Trust Alliance Censuses. All comparisons exclude land held in Alaska.
Table 2
Characteristics of Land Trust Data Sets
Data Set
TNC
NCED
LTA
Annual
panel?
National
coverage of
easements?
Indicates
donations vs.
purchases?
Indicates month
of Acquisition
Yes
Yes
No (periodic)
Yes
Yes, with gaps
Yes
Yes
No
Partially
Yes
Partially
No
Notes: The NCED data are available at http://conservationeasement.us/about. The Nature Conservancy (TNC)
and Land Trust Alliance (LTA) data were provided to us by database managers of those organizations.
Table 3
Summary Statistics of State-Level Annual Panel of Land Trust Acquisitions
The Nature Conservancy (TNC)
All
(1)
Purchased
(2)
Donated
(3)
National Conservation Easement
Data (NCED)
All
(4)
December
(5)
Easements Count
Mean
Min
Max
1.60
0 [635]
31
0.454
0 [972]
14
1.15
0 [754]
31
12.36
0 [403]
255
3.65
0 [697]
92
Easements Acres
Mean
Min
Max
2,439
0
244,753
783.5
0
149,993
1,655
0
244,753
4,953
0
610,814
1,634
0
141,946
Notes: The summary statistics are for a state-level panel spanning 1987 through 2012 (N = 1300, t = 26, i=50).
The number in brackets indicates the number of observations for which the value is zero. Many conservation
easements in the NCED dataset (66%) are missing information about the month in which the easement was
acquired. Column 3 combines ‘All Gift’ and ‘Partial Gift’ categories from TNC. The source for TNC data is
data sent to us by the database manager. The NCED data were downloaded from
http://conservationeasement.us/, (updated in July 2015).
Table 4
Fixed Effects Estimates of the Number of Easement Acquisitions
TNC All
TNC
Purchased
(3)
TNC All
(1)
TNC
Donated
(2)
(4)
TNC
Donated
(5)
TNC
Purchased
(6)
NCED
All
(7)
NCED
December
(8)
NCED
All
(9)
NCED
December
(10)
-0.007
(0.474)
-0.063
(0.414)
0.046
(0.261)
-0.510
(0.392)
-0.594
(0.452)
0.542
(0.357)
0.461
(0.901)
-0.041
(0.808)
0.091
(0.467)
0.004
(0.632)
-1.289**
(0.610)
-1.346**
(0.578)
-0.618
(0.461)
-1.287**
(0.493)
-1.482*
(0.740)
0.082
(0.329)
-0.502
(0.460)
-1.225*
(0.633)
-2.004***
(0.640)
-1.729**
(0.733)
Δ Price of Const (β3)
-0.418
(0.347)
-0.495
(0.355)
0.996**
(0.459)
-0.959***
(0.292)
-0.918***
(0.334)
0.462*
(0.566)
-2.426***
(0.566)
-2.158***
(0.590)
-1.498**
(0.695)
-1.679***
(0.618)
First period response (β2+β3)
-1.71***
(0.543)
-1.84***
(0.495)
0.378
(0.256)
-2.25***
(0.436)
-2.40***
(0.592)
0.544
(0.441)
-2.93***
(0.482)
-3.38***
(0.432)
-3.50***
(0.499)
-3.41***
(0.631)
-0.043*
0.405**
-0.077
0.697
0.122
-0.005
-0.053**
0.344**
-0.033
0.858
0.390
-0.008
0.012
0.109
-0.110
-0.396
0.003
-0.001
-0.028
0.259
-0.138
1.154
1.977
-0.003
-0.039
0.079
-0.337
1.384
2.095
-0.011
0.017
0.165
0.288
-0.309
-0.657
0.021
-0.096***
-0.331
0.662
-1.197
-0.657
0.021
-0.082***
-0.145
0.193
-0.429
-0.407
0.013
-0.009
0.033
0.639**
1.234
-1.827
0.006
0.003
0.045
0.314
2.189*
-6.254**
-0.006
State fixed effects
Year fixed effects
State specific trends
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Adjusted R2 (within)
N
0.144
1000
0.136
1000
0.064
1000
0.222
1000
0.201
1000
0.346
1000
0.346
1000
0.243
1000
0.530
1000
0.419
1000
ΔPrice of Const+1 (β1)
Price of Const (β2)
Controls
Land Price Index
LN Forest Income
LN Farm Income
LN Per Capita Income
LN Population
Govt. Easement Acres
Notes: * p<0.1; ** p<.05; *** p<.01. The standard errors presented in parentheses are clustered at the state level. The observations are state-year combinations from 1992
through 2012. The dependent variable is the count of easements, transformed by the inverse hyberbolic sine function.
Table 5
Fixed Effects Estimates of the Acreage of Easement Acquisitions
TNC All
TNC
Purchased
(3)
TNC All
(1)
TNC
Donated
(2)
(4)
TNC
Donated
(5)
TNC
Purchased
(6)
NCED
All
(7)
NCED
December
(8)
NCED
All
(9)
NCED
December
(10)
ΔPrice of Const+1 (β1)
2.103
(1.416)
1.814
(1.388)
2.487
(1.522)
1.497
(1.756)
0.986
(1.617)
3.635*
(2.159)
2.746
(1.850)
-0.160
(1.836)
1.208
(0.928)
-0.325
(1.600)
Price of Const (β2)
-2.305
(2.164)
-2.525
(1.948)
-3.578
(2.919)
-0.873
(1.194)
-1.806
(1.566)
1.076
(1.377)
-0.140
(0.941)
-1.635
(1.314)
-5.116**
(2.044)
-3.206*
(1.806)
Δ Price of Const (β3)
-4.235
(3.508)
-3.752
(3.525)
5.643**
(2.389)
-6.145*
(3.099)
-5.178
(3.312)
2.533
(1.522)
-3.475***
(1.246)
-3.948**
(1.701)
-0.781
(1.561)
-2.823
(1.799)
-6.540***
(1.886)
-6.277***
(2.118)
2.065
(1.498)
-7.018*
(3.673)
-6.98*
(3.583)
3.609*
(2.050)
-3.615***
(1.300)
-5.583***
(1.397)
-5.897***
(2.171)
-6.029***
(2.144)
-0.064
1.362*
0.185
2.162
-2.934
-0.018
-0.095
1.174
0.364
2.090
0.777
-0.028
0.057
0.631
-0.614
-2.606
-0.998
-0.008
-0.076
0.871
-0.902
4.653
7.889
0.004
-0.058
-0.440
-0.970
3.626
12.348
-0.038
-0.030
1.055
0.382
-0.165
-2.136
0.054
-0.124*
-0.911
2.370**
-1.812
-2.648
0.005
-0.173**
-0.548
1.112
0.925
-2.235
-0.025
0.092
0.643
1.704*
-0.520
2.202
-0.019
0.103
0.343
0.488
6.778
-2.950**
-0.071*
State fixed effects
Year fixed effects
State specific trends
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Adjusted R2 (within)
N
0.090
1000
0.077
1000
0.068
1000
0.134
1000
0.119
1000
0.138
1000
0.222
1000
0.189
1000
0.349
1000
0.305
1000
First period response (β2+β3)
Controls
Land Price Index
LN Forest Income
LN Farm Income
LN Per Capita Income
LN Population
Govt. Easement Acres
Notes: * p<0.1; ** p<.05; *** p<.01. The standard errors presented in parentheses are clustered at the state level. The observations are state-year combinations from 1992
through 2012. The dependent variable is the count of easements, transformed by the inverse hyberbolic sine function.
Table 6: Robustness Checks
Y= Easement Counts
A. Baseline
ΔPrice of Const+1 (β1)
Price of Const (β2)
Δ Price of Const (β3)
Observations
TNC All
TNC
Donated
NCED
All
NCED
Dec.
TNC All
TNC
Donated
NCED
All
NCED
Dec.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
-0.510
-1.287**
-0.959***
1000
-0.594
-1.482*
-0.918***
1000
0.091
-2.004***
-1.498**
1000
0.004
-1.729**
-1.679***
1000
1.497
-0.873
-6.145*
1000
0.986
-1.806
-5.178
1000
1.208
-5.116**
-0.781
1000
-0.325
-3.206*
-2.823
1000
0.048
-1.616***
-1.629**
1000
0.046
-1.417***
-1.497***
1000
1.032
-4.677**
-0.787
1000
0.254
-2.121
-2.488
1000
B. State Weights by NCED Completion
ΔPrice of Const+1 (β1)
Price of Const (β2)
Δ Price of Const (β3)
Observations
C. Placebo Timing
ΔPrice of Const+1 (β1)
Price of Const (β2)
Δ Price of Const (β3)
Observations
Y= Easement Acres
0.988
1.562
-2.446
882
1.258
0.940
-2.542
882
0.300
-0.608
0.327
882
0.184
-0.589
0.523
882
2.931
9.780
-6.567
882
3.123
6.186
-6.650
882
2.892
-0.331
-1.274
882
0.343
-0.311
-2.061
882
-0.508
-1.287**
-0.956***
1000
-0.591
-1.482**
-0.912***
1000
0.110
-2.004***
-1.472**
1000
0.015
-1.729**
-1.663**
1000
1.586
-0.874
-6.021*
1000
1.048
-1.808
-5.092
1000
1.303
-5.118**
-0.649
1000
-0.266
-3.207*
-2.740
1000
ΔPrice of Const+1 (β1)
Price of Const (β2)
Δ Price of Const (β3)
Observations
-0.439
-1.511***
-0.849**
320
-0.642
-1.625*
-0.745
320
0.216
-2.380***
-1.248*
320
0.049
-1.730*
-1.726**
320
1.451
-2.736*
-5.143
320
1.125
-2.535
-4.516
320
2.517**
-6.441***
0.007
320
0.860
-3.304
-3.186
320
F. Tax Credit States
ΔPrice of Const+1 (β1)
Price of Const (β2)
Δ Price of Const (β3)
Observations
-0.532
-1.564**
-0.845
220
-0.497
-1.809**
-0.653
220
0.343
-2.420***
-1.276
220
0.119
-1.836**
-1.611*
220
1.250
-2.444
-5.155
220
1.362
-3.191
-3.904
220
3.084*
-5.755**
-0.281
220
1.091
-3.454
-2.388
220
D. Estate Tax Control
ΔPrice of Const+1 (β1)
Price of Const (β2)
Δ Price of Const (β3)
Observations
E. ‘Almost’ Tax Credit
Counterfactual States
G. Omit Tax Credit Obs.
ΔPrice of Const+1 (β1)
-1.173
-0.597
-1.247
-1.346
5.836
-0.641
-2.609
-4.657
Price of Const (β2)
-1.567
-2.139
-2.580
-2.045
6.633
-0.835
-1.132
-0.836
Δ Price of Const (β3)
-2.671
-2.006
-0.818
-2.488
-13.873
-5.101
-7.275
-12.019
Observations
882
882
882
882
882
882
882
882
*
**
***
Notes: p<0.1; p<.05; p<.01. The standard errors presented in parentheses are clustered at the state level. All
specifications include year effects, state fixed effects, controls, and state-specific time trends. Panel A shows the baseline
results from columns 5-6 and 9-10 of tables 4 and 5. Panel B weights each state by our estimate of how complete the NCED
easement data coverage is for each state. Panel C moves treatment up two years before the actual year of a new tax credit.
Panel D adds an indicator for whether or not a state followed the federal phase out of estate taxes during 2002-2005. Panel E
trims the sample to include only states with tax credits and states that attempted to pass credits. Panel F includes only those
states with tax credits. Panel G omits state-year combinations during which a tax credit program was in effect, and the year
preceding a new tax credit program.
Table 7: Simulated Changes in Donated Acre Flows due to Introduction of
Tax Credit Programs
Simulated Percent Changes4
State
Year of
Tax Credit
Credit
Percentage
Dollar
Years to
Limit Transferable Carry Over
Price of
Short-run
Conservation
Acres
Long-run
Acres
NC1
1989
25%
25K
No
5
-5.3
31.4
27.2
CO
DE
2000
2000
100%
40%
100K
50K
Yes
No
20
5
-30.0
-1.4
199.9
8.4
168.2
7.3
VA
CA
2000
2001
50%
55%
50K
1,000K
Yes
No
5
8
-16.5
-6.4
101.0
37.7
86.8
32.6
MD
SC
2001
2001
100%
25%
80K
1,000K
No
Yes
15
50
-9.7
-34.7
57.8
240.2
50.0
200.2
NM
GA
2004
2006
50%
25%
100K
250K
No
Yes
5
5
-13.1
-5.1
78.8
30.2
68.0
26.1
IA
MA2
2008
2011
50%
50%
100K
50K
No
No
20
0
-18.7
-16.2
115.8
99.2
99.2
85.3
USA3
2006
changes in deductibility rules3
-7.5
44.7
38.7
Notes: (1) North Carolina's tax credit program began in 1983, before our sample period. The table reports a change in 1989
from a $5K limit to a $25K limit. (2) Massachusetts' tax credits are non-transferrable. They are, however, refundable, which
in the calculator makes them effectively transferrable. (3) In 2006, the federal code changed, increasing the percent-of-AGI
limit from 50% to 100% and the carryover limit from 5 to 15 years for qualified farmers and ranchers. (4) Percentage
changes are calculated as geometric means of the discrete rates of growth using the initial donation flow as a base and the
subsequent donation flow as a base.
Table 8: Descriptive Statistics of Strategic Conservation
Number of Easements
Percent of a Trust’s
Easements
Mean
St. Dev
Number of
Trusts
Mean
St. Dev
Acquisition Method
All
Donated
Purchased
Bargain Sale
29.76
23.88
2.946
2.934
97.76
86.46
11.64
14.71
79.47
13.64
6.883
32.30
27.81
18.45
631
631
631
631
Conservation Quality
Easements in Priority Area
23.79
96.64
75.25
30.60
548
Notes: Data come from the 2005 Land Trust Alliance survey of trusts. Observations included are those inferred to have
responded to the relevant question. The stock of all easements was reported by survey participants. The stock of donated,
bargain sales, and purchased easements are estimated by multiplying the reported estimated percentage of easements
acquired through each method by the reported stock of all easements.
Table 9: Trust-Level OLS Regressions of Strategic Conservation
Y = Percent of Easements in Priority Area
(1)
(2)
(3)
(4)
-0.172***
(0.041)
-0.169**
(0.078)
Percent Bargain Sales
-0.086
(0.067)
-0.053
(0.097)
-0.089
(0.067)
-0.054
(0.089)
Number of All Easements
0.011**
(0.006)
0.011**
(0.002)
0.011*
(0.006)
0.009**
(0.004)
Interactions with Price of Conservation
% Donated x Indicator for 1st PCon Quartile
(lowest price of conservation)
-0.163***
(0.060)
-0.113
(0.096)
% Donated x Indicator for 2nd PCon Quartile
-0.167***
(0.051)
-0.106
(0.079)
% Donated x Indicator for 3rd PCon Quartile
-0.122**
(0.051)
-0.100
(0.084)
% Donated x Indicator for 4th PCon Quartile
(highest price of conservation)
-0.218***
(0.049)
-0.300***
(0.084)
Percent Donated
Constant
Weighted by Number of Easements
Observations
Adjusted R2
88.283***
(3.315)
87.734***
(6.561)
88.255***
(3.320)
88.390***
(6.641)
No
432
0.022
Yes
432
0.065
No
432
0.020
Yes
432
0.089
Notes: * p<0.1; ** p<.05; *** p<.01. Robust standard errors are presented in parentheses. Data come from the 2005 Land Trust
Alliance survey of trusts. Observations included are those inferred to have responded to all of the relevant questions. The
indicator for the 1st PCons quartile equals 1 for states that were in the lowest quartile (25th percentile) for the price of
conservation, averaged over 2000-2005. This quartile includes states with an average price of conservation under 0.575, for
the AGI = $100,000, Donation = $500,000 scenario. The definitions for the other quartiles are similar.